APPENDIX 17A. REGULATORY IMPACT AN ALYSIS: SUPPORTING

MATERIALS

TABLE OF CO NTENTS

17A.1 INTRODUCTION

................................ ................................ ................................ 17A

- 2

17A.2 MARKET SHARE ANNUAL INCREASES BY POLICY

................................ . 17A

- 3

17A.3 NIA

- RIA INTEGRATED MODEL

................................ ................................ ...... 17A

- 4

17A.4 CONSUMER REBATE POLI CY MARKET PENETRATIO N CURVES

......... 17A

- 4

17A .4.1 Introduction

................................ ................................ .......................... 17A

- 4

17A.4.2 Adjustment of XENERGY Penetration Curves

................................ ... 17A

- 6

17A.4.3 Interpolation of Penetration Curves

................................ ..................... 17A

- 7

17A.5 CONSUMER REBATE PROG RAMS

................................ ................................ . 17A

- 8

17A.6 FEDERAL AND STATE TA X CREDITS

................................ ........................... 17A

- 9

17A.6.1 Federal Tax Credits for Consumers

................................ ...................... 17A

- 9

17A.6.2 Federal Tax Credits for Manufacturers

................................ .............. 17A

- 10

17A.6.3 State Tax Credits

................................ ................................ ................ 17A

- 11

LIST OF TABLES

Table 17A.2.1 Annual Increases in Market Shares (%) Attributable to Alternative Policy Measures for S PVAC <65

................................ ............................. 17A

- 3

Table 17A.5.1 Rebates for CUAC < 65 KBtu

................................ ................................ .. 17A

- 8

LIST OF FIGUR E S

Figure 17A.4.1 S

- Curves Showing Effects of External and Internal Sources on Adoption of New Technologies

................................ ................................ 17A

- 6

17A

- iAPPENDIX 17A. REGULATORY IMPACT AN ALYSIS: SUPPORTING M ATERIALS

17A.1 INTRODUCTION

This appendix contains sections discussing the following topics:

• Projections of annual market share increases for the alternative policies;

• NIA

- RIA Integrated Model;

• XENERGY penetration curves used to analyze consumer rebates, including:

o Background material,

o DOE’s adjustment of these curves for this analysis, and

o The m ethod DOE used for interpolating the curves;

• Detailed tables of rebates offered for the considered products; and

• Background material on Federal and state tax credits for appliances

.

17A

- 217A.2 MARKET SHARE ANNUAL INCREASES BY POLICY

Table 17A.2.1 sh ow s the annual increases in market shares of SPVUs meeting the target efficiency level for the proposed TSL (TSL 2 )

. DOE used these market share increases as inputs

to the NIA

- RIA spreadsheet model.

Table 17A.2.1 Annual Increases in Mar ket Shares (%) Attributable to Alternative Policy Measures for SPVAC <65

Year Consumer

Rebates Consumer

Tax Credits Manufacturer

Tax Credits Voluntary Energy Efficiency

Targets Early Replacement

2019 0.8 0.5 0.2 0.6 0.022

2020 0.8 0.5 0.2 0.6 0.021

2021 0.8 0.5 0.2 0.6 0.021

2022 0.8 0.5 0.2 0.6 0.020

2023 0.8 0.5 0.2 0.6 0.019

2024 0.8 0.5 0.2 0.6 0.018

2025 0.8 0.5 0.2 0.6 0.017

2026 0.8 0.5 0.2 0.6 0.016

2027 0.8 0.5 0.2 0.6 0.013

2028 0.8 0.5 0.2 0.6 0.011

2029 0.8 0.5 0.2 0.6 0.008

2030 0.8 0.5 0.2 0.6 0.005

2031 0.8 0.5 0.2 0.6 0.003

2032 0.8 0.5 0.2 0.6 0.002

2033 0.8 0.5 0.2 0.6 0.000

2034 0.8 0.5 0.2 0.6 0.000

2035 0.8 0.5 0.2 0.6 0.000

2036 0.8 0.5 0.2 0.6 0.000

2037 0.8 0.5 0.2 0.6 0.000

2038 0.8 0.5 0.2 0.6 0.000

2039 0.8 0.5 0.2 0.6 0.000

2040 0.8 0.5 0.2 0.6 0.000

2041 0.8 0.5 0.2 0.6 0.000

2042 0.8 0.5 0.2 0.6 0.000

2043 0.8 0.5 0.2 0.6 0.000

2044 0.8 0.5 0.2 0.6 0.000

2045 0.8 0.5 0.2 0.6 0.000

2046 0.8 0.5 0.2 0.6 0.000

2047 0.8 0.5 0.2 0.6 0.000

2048 0.8 0.5 0.2 0.6 0.000

17A

- 317A.3 NIA

- RIA INTEGRATED MODEL

For this analysis, DOE used its integrated NIA

- RIA a model appro ach that built on the

NIA model discussed in Chapter 10 and documented in Appendix 10A .The resulting integrated

NIA

- RIA model featured both the NIA analysis inputs and results and the RIA inputs and had

the capability to generate results for each of the RIA polic ies. A separate module produced results summaries for the tables and figures in the RIA document. For the RIA methodology

documentation in C hapter 17

, t he module created summaries of parameters calculated by the

model for the consumer rebates policy, generated its penetration curves (discussed in

S ection 17A.4.3 below)

, and reported market s hare impacts for the rebate and tax cred it policies by product class. For the RIA results reported in C hapter 17 , the module produced graphs of the

market sh are increases resulting from each of the policies analyzed and created summary tables for the national energy savings (NES) and net present value (NPV) results

. This module also generated tables of market share increases for each policy reported in S ection 17A.2 of this Appendix

.

17A.4 CONSUMER REBATE POLI CY MARKET PENETRATIO N CURVES

This section first discusses the theoretical basis for the market penetratio n curves that DOE used to analyze the Consumer Rebates policy. Next it discusses the adjustments it made to the maximum penetration rates. It then refers to the method it used to develop interpolated penetration curves for each specific product class and e fficiency level in the analysis. The resulting curve s for SPVAC <65 product class is in C hapter 17

.

17A.4.1 Introduction

XENERGY, Inc. b , developed a re

- parameterized, mixed

- source information diffusion model to estimate market impacts induced by financial incentives for purchasing energy efficient appliance s. 1 The basic premise of the mixed

- source model is that information diffusion drives the adoption of technology.

Extensive economic literature describes the diffusion of new products as technologies evolve. Some research focuses primarily on developing analytical models of diffusion patterns applicable to individual consumers or to technologies from competing firms

. 2

, 3

, 4 One study records researchers’ attempts to investigate the factors that drive diffusion processes

. 5 Because a new product generally has its own distinct characteristics, few studies have b een able to conclusively develop a universally applicable model. Some key findings, however, generally are accepted in academia and industry.

One accepted finding is that, regardless of their economic benefits and technological merits, new technologies are unlikely to be adopted by all potential users. For many products, a

a NIA = national impact analysis; RIA = regulatory impact analysis

b XENERGY is now owned by DNV GL. ( www.dnvgl.com/energy/ )

17A

- 4ceiling must be placed on the adoption rate. A second conclusion is that not all adopters purchase new products at the same time: some act quickly after a new product is introduced; ot hers wait for the product to mature. Third, diffusion processes can be characterized approximately by asymmetric S

- curves that depict three stages of diffusion: starting, accelerating, and decreasing (as the adoption ceiling is approached).

A so

- called e pidemic model of diffusion is used widely in marketing and social studies. The epidemic model assumes that (1) all consumers place identical value on the benefits of a new product, and (2) the cost of a new product is constant or declines monotonically ove r time. What induces a consumer to purchase a new product is information about the availability and benefits of the product. In other words, information diffusion drives consumers’ adoption of a

new product

. 3 The model incorporates information diffusion from both internal sources (spread by word of mouth from early adopters to prospective adopters) and external sources (the “announcement effect” produced by government agencies, institutions, or commercial advertising). The model incorporates both internal and external sources by combining a logistic function with an exponential function. 4

, 5

The relative degree of influence from the internal and external sources determines the general shape of the diffusion curve for a specific product. 4

, 5 If adoption of a product is

influenced primarily by external sources of information (the announcement effect), for instance, a high rate of diffusion occurs at the beginning of the process. In this scenario, external sources provide immediate information exposure to a significant number of pro spective adopters. In contrast, internal sources (such as a network of prospective adopters) are relatively small in size and reach, producing a more gradual exposure to prospective adopters. Graphically speaking, information diffusion dominated by externa l sources is represented by a concave curve (the exponential curve in Figure 17A.4.1 ). If adoption of a new product is influenced most strongly by internal sources of information, the number of adopters increases gradually, forming a convex curve (the logistic curve in Figure 17A.4.1 ).

17A

- 5Figure 17A.4.1 S

- Curves Showing Effects of External an d Internal Sources on Adoption of New Technologies

17A.4.2 Adjustment of XENERGY Penetration Curves

In consultation with the primary authors of the 2002 XENERGY study who later conducted similar California studies, DOE made some adjustments to XENERGY’s original implementation (penetration) curves. 6 The experiences with utility programs since the XENERGY study indicate that incentive programs have difficulty achieving penetration rates as high as 80 percent. Consumer response is limited by barriers created by consumer utility issues

and other non

- economic factors. DOE therefore adjusted the maximum penetration parameters for some of the curves from 80 percent to the following levels:

Moderate Barriers: 70% High Barriers: 60%

Extreme ly High Barriers: 50%

The low barriers and no barriers curves (the latter used only when a product has a very high base

- case

- market share) remained, respectively, with 80 percent and 100 percent as their maximum penetration rates. For the interpolated p enetration curves (discussed below), DOE set

the no barriers and extremely high barriers curves as the upper and lower bounds, respectively, for any benefit/cost ratio points higher or lower than the curves. It set another constraint such

17A

- 6that the policy c ase market share cannot be great than 100 percent, as might occur for products with high base case market shares of the target

- level technology.

17A.4.3 Interpolation of Penetration Curves

As discussed above, the XENERGY penetration (implementation) curves follow ed a functional form to estimate the market implementation rate caused by energy efficiency

measures such as consumer rebates. c The XENERGY report presents five reference market implementation curves that vary according to the level of market barriers to t echnology penetration. 1 Such curves have been used by DOE in the Regulatory Impact Analyses for rulemakings for appliance energy efficiency standards to estimate market share increases in response to rebate programs. d They provide a framework for evaluating technology penetration, yet require matching the studied market to the curve that best represents it. This approximate matching can introduce some i naccuracy to the analysis.

Blum et al (2011, Appendix A) 7 presents an alternative approach to such evaluation: a method to estimate market implementation rates more accurately by performing interpolations of

the reference curves. The referred report describes the market implementation rate function and the reference curves, the method to calibrate the function to a given market, and the limitations

of the method.

c The RIA chapter refers to these curves as penetration curves . This section, in references to the original source, uses

the term implementation curve

. d DOE has also used this method to estimate market share increase s resulting from consumer tax credit and manufacturer tax credit programs, since the effects of tax credits on market s can be considered proportional to the

rebate impacts

.

17A

- 717A.5 CONSUMER REBATE PROGRAMS

Since DOE did no t find any rebate programs for SPVUs, it searched for rebates for single package commercial unitary air conditioners (CUACs) as a related product. Some organizations nationwide, comprising electric utilities and municipal and regional agencies, have rebat e programs for CUAC s

. DOE found 4 rebate programs from 4 o rganizations that offered rebates

for single package units with capacities less than 65 ,000 Btus that met various efficiency criteria.

DOE selected rebate programs that had EER ratings only. It did n ot include programs that had SEER ratings, reasoning that those units would be less similar to SPVUs. Table 17 A.5.1 provides the organizations’ names, states, rebate amounts , EER levels, and program websites. If there is more than one entry for an organiza tion, that organization offers different rebate amounts depending on efficiency level

. R ebates are per ton of capacity, so DOE calculated the rebate per unit using a 3

- ton unit as the representative unit. DOE then calculated the average rebate across all p rograms. The rebate amount DOE calculated for SPVUs is $ 205.71 (in 2013 $).

Table 17A.5.1 Rebates for CUAC < 65 KBtu

Utility St ate Rebate $ EER Website

SRP AZ $60/ton 11.6 http://www.srpnet.com/energy/powerwise/business/pdfx/standardcont ractor/FY13HVACEquipmentCatalog.pdf

SRP AZ $85/ton 12.0 http://www.duke

- energy.com/pdfs/NC_HVAC.pdf

Duke Energy KY $25/ton 14.0 http://www.austinenergy.com/EnergyEfficiency/Programs/Rebates/Co mmercial/CommercialEnergy/DXGuidelinesSchedule.pdf
Duke Energy NC $25/ton 12.0 http://www.srpnet.com/energy/powerwise/business/pdfx/standardcont ractor/FY13HVACEquipmentCatalog.pdf
Duke Energy NC $45/ton 12.5 http://www.austinenergy.com/EnergyEfficiency/Programs/Rebates/Co mmercial/CommercialEnergy/DXGuidelinesSchedule.pdf
Efficiency Maine ME $150/ton 12.0 http://www.srpnet.com/energy/powerwise/business/pdfx/standardcont ractor/FY13HVACEquipmentCatalog.pdf
Efficiency Vermont VT $90/ton 12.0 http://www.efficiencymaine.com/docs/at_work/EMBPPrescCashIncen tives.pdf

17A

- 817A.6 FEDERAL AND STATE TA X CREDITS

This section summarizes the Federal and State tax credits available to consumers who purchase energy efficient appliances. This section also describes tax credits available to manufacturers who produce certain energy efficient appliances.

17A.6.1 Federal Tax Credits for Consumers

EPACT 2005 included Federal tax credits f or consumers who installed efficient air conditioners or heat pumps; gas, oil and propane furnaces and boilers ; furnace fans; and/or gas, oil, or electric heat pump water heaters in new or existing homes. 8

, 9 These tax credits were in effect in 2006 and 2007, expired in 2008, and were reinstated for 2009

– 2010 by the American Recovery and Reinvestment Act (ARRA). 10 There was a $1,500 cap on the credit per home, including the amount received for insulation, windows, and air and duct sealing. Congress extended this provision for 2011, with some modifications to eligibility requirements, and reductions in the cap to $50 0 per home

. The American Taxpayer Relief Act of 2012 extended, with some modifications, residential tax credits for air conditioners, heat pumps, furnaces, and

water heaters placed in service between January 1, 2012 and December 31, 2013. 8

, 11

The tax credit for furnace fans was $50 in 20 1 1, after which it expired.

The importance of the Fed eral tax credits has been emphasized in research in the residential heating industry on the impacts of the relatively large credits that were available for HVAC (heating, ventilating, and air conditioning) equipment

. I n a survey of HVAC distributors conducted by Vermont Energy Inve stment Corporation, respondents indicated that the ample

credit had had a notable impact on sal es of higher

- efficiency heating and cooling equipment

. Some distributors combined the Federal tax credits with manufacturer re bates and ut ility

program rebates for a greater consumer incentive. However, when the amount of the Federal tax

credit was reduced , smaller utility rebate incent ives had not ind uced the same levels of equipment sales increases

. T h e decrease in incentive size from a $1,500 cap in 2009

- 20 10 to a $500 cap in 2011 , during a period when the economy continued to be sluggish, resulted in a

decline in total sales of residential HVAC products

. Distributors stated that an incentive needed to cover 25 to 75 percent of the incremental cost of the efficient equipment to influence

consumer choice. The industry publication “ 2011 HVAC Review and Outlook ” noted a decline

in sa les of air conditioning units with >14 SEER in 2011 and a return in sales of units with >16 SEER to 2009 levels (after an increase in 2010). The l arge majority of distributor observed no impacts from the utility p rograms with their lower rebate amounts ava ilable in 2011. Distributors also commented on the advantages of the Federal tax credit being nationwide in contrast to utility rebate programs that target regional markets. 12

, 13

In an effort to evaluate the potential impact of a Federal appliance tax credit program

, DOE reviewed Internal Revenue Service (IRS) data on the numbers of taxpayers who claimed

the tax credits durin g tax years 2006 and 2007. It estimated the percentage of taxpayers who filed
Form 5695, Residential Energy Credits

. 14 It also estimated the percentage of taxpayers with
entries under Form 5695’s section 3, Residential energy property costs , line 3b, qualified natural gas, propane, or oil furnace or hot water boiler . DOE reasoned that the percentage of taxpayers

17A

- 9with an en try on Line 3b could serve as a rough indication of the potential of taxpayer participation in a Federal tax credit program for furnaces during the initial program years. DOE found that of all residential taxpayers filing tax returns, 0.8 percent in 2006 a nd 0.6 percent in 2007, claimed a credit for a furnace or boiler. DOE further found that the percentages of those filing Form 5695 for any qualifying energy property expenditure (which also included installation of efficient windows, doors and roofs) were 3.1 and 3.2 percent in 2006 and 2007 respectively.

DOE also reviewed data from an earlier Federal energy conservation tax credit program in place in the 1980s. While this tax credit was available from 1979 through 1985, DOE located data for only the fi rst three years of the program

. 15

, 16

, 17 For those three years

- 1979, 1980, and

1981

- the percentages of taxpayers filing Form 5695 were 6.4 percent, 5.2 percent, and 4.9 percent. Given that the data from this earlier tax credit program were not disaggregated by type of energy property, this data series served only to indicate a possible trend of greater participation in the initial program year, followed by slightly smaller participation in subsequent years. However, DOE did not find detailed analysis of this program to indicate the possible reasons for such a trend. Also, this trend varies fro m the more stable trend shown in the EPAct 2005 energy tax credit program data for its first two program years.

As discussed in C hapter 17, DOE analyzed the percentage of participation in consumer tax credit programs using its estimates of consumer parti cipation in rebate programs that was based on benefit/cost data specific to each product class. Hence it was difficult to compare these detailed estimates to the more general data analysis described above from the existing Federal tax credit program, or to use the IRS data analysis in its consumer tax credit analysis.

17A.6.2 Federal Tax Credits for Manufacturers

EPACT 2005 provided Federal Energy Efficient Appliance Credits to manufacturers that produced high

- efficiency refrigerators, clothes washers, and dishwash ers in 2006 and 2007. 18

The Emergency Economic Stabilization Act of 2008 19 amended the credits and extended them through 2010. The credits were extended again to 2011 with modifications in the eligibility requirements. Manufacturer t ax credits were extended again, by the American Taxpayer Relief

Act of 2012 , for clothes washers, refrigerators, and dishwashers manufactured between January
1, 2012 and December 31, 2013. 20

Manufacturers who produce these appliances receive the credits for increasing their production of qualifying appliances. These credits had sev eral efficiency tiers in 2011. F or 2012

- 2013, credits for the higher tiers remain but were eliminated for the lowe st (least efficient) tiers

for cloth es washers and dishwashers

. 11 The credit amounts applied to each unit manufactured. The credit to manufacturers of qualifying clothes washers, refrigerators and dishwashers wa s

cap ped at $75 million for the period of 2008

- 2010. However, the most efficient refrigerator (30%) and clothes washer (2.2 MEF/4.5 wcf) models was not subject to the ca p. The credit to

manufacturers wa s capped at $25 million for 2011, with t he most efficient r efrigerators (35%)

and clothe s washers (2.8 MEF/3.5 WCF) exempted from this cap. 21

17A

- 1017A.6.3 State Tax Credits

The States of Oregon and Montana have offered consumer tax credits for efficient appliances for several years, and the States of Kentucky, Michigan an d Indiana began offering such credits in 2009. The Oregon Department of Energy (ODOE) has disaggregated data on taxpayer participation in credits for eligible products. ( See the discussion in C hapter 17

, S ection

1 7 .3.3, on tax credit data for clothes washers.) Montana’s Department of Revenue does not disaggregate participation data by appliance, although DOE reviewed Montana's overall participation trends and found them congruent with its analysis of Oregon's clothes washer tax

credits.

Oregon’s Resi dential Energy Tax Credit (RE TC) was created in 1977. T he Oregon legislature expanded the RETC program in 1997 to include residential refrigerators, clothes washers, and dishwashers, which significantly increased participation in the program . The

program s ubsequently added credits for high

- efficiency heat pump systems, air conditioners, and water heaters (2001); furnaces and boilers (2002); and duct/air sealing, fuel cells, heat recovery, and renewable energy equipment. Beginning in 2012 a Tax Credit Extens ion Bill (HB3672) eliminated refrigerators, clothes washers, dishwashers, air conditioners, and boilers from the RETC program, leaving credits for water heaters, furnaces, heat pumps, tankless water heaters

, and heat pump water heaters. 22

, 23 Those technologies recognized by the Oregon Department of Energy as “premium efficiency” are eligi ble for tax credit of $0.60 per kWh saved in the first year (up to $1,500). 22

, 24

Montana has had an Energy Conservation Tax Credit for residential measures since

1998. 25 The tax credit covers various residential energy and water efficient products, including split system central air conditioning; package system central air conditioning; split system air source heat pumps; package system heat pumps; natural gas, propane, or oil furnaces; hot water boilers; advanced main air circulating fans ; heat recovery ventilators; gas, oil, or propane water heaters; electric heat pump water heaters; low

- flow showerheads and faucets ; light fixtures ; and

controls. In 2002 the amount of the credit was increased from 5 percent of product costs (up to $150) t o 25 percent (up to $500) per taxpayer. The credit can be used for products installed in new construction or remodeling projects. The tax credit covers only that part of the cost and

materials that exceed established standards of construction.

17A

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- 14